Machine-to-Machine (M2M) devices are in general devices that have a sensing, actuating, or any automated data-generating task that runs without human intervention and has connectivity to a backbone network, which aggregates and processes data from many sources. M2M systems, in turn, refer e.g. systems which are empowered by M2M devices, including an end-to-end platform for providing enhanced and homogenized access to the M2M data.
M2M is nowadays considered an integral part of the Internet-of-Things and has a wide range of application such as industrial automation, logistics, etc., not only for monitoring but also for control purposes.
Since for example when a new M2M application is launched new devices, gateway software modules or databases which are dedicated to this application and service needs are deployed. These so-called verticals “enrich” the M2M system through all levels reaching from M2M devices D to the applications A. The latest trends however suggest a transition towards so-called horizontals, i.e. configurable M2M platforms with technology abstraction layers, extended functionalities, etc. which continuously and proactively maintain knowledge and control of the physical world, providing an application programming interface API with which various types of new M2M applications A can be developed without the need of re-engineering the lower levels.
However one of the problems of these horizontal platforms is, that it is much more difficult for operators to maintain configurations covering their changing needs and serve their dynamic goals. The reason for that is that—compared to verticals—horizontals have the following characteristics: They serve various domains resulting in a bigger number of technologies to be supported, i.e. numerous and more complex configuration parameters. Further it is more difficult to know or to calculate configuration combinations satisfying current goals. A further problem is the usage of different type of gateways which need to be configured differently: A bigger system scale results in an increased workload for configuration maintenance and an increased probability to save costs. Further an increased degree of expertise is required by an operator in order to configure the M2M system efficiently. Even further various restrictions for the access to gateways and/or their configurations may be present since the might provided by third parties.
Conventional configuration methods usually rely on defining standard techniques for remote parameter settings. Another conventional method is to adapt automation approaches for autonomic computing, for example self-management, etc. Such conventional techniques for remote setting of system parameters, for example are being disclosed in US 2007 022 0093 A1 providing a remote configuration of gateway environments such as OSGi or in the non-patent literature of TR-069 Amendment 5, CPE WAN Management Protocol, Broadband Forum, 2013 showing a remote setting of gateway parameters.
However, these conventional methods cannot provide a higher degree of automation. Further active remote configuration suffers from the problem that the operations are unaware of the configuration. Further the heterogeneity of the gateways in the big system size cause problems when applying these conventional methods.
In U.S. Pat. No. 6,515,957 B1 a configuration of IP translation functions is shown. In US 2005/0157730 A1 an auto-configuration management of gateways in heterogeneous networks is shown. However these conventional methods are very strongly bound to the specific technology for example IP, IETF, iSCSI, i.e. they are not directed to M2M systems.
Further methods for autonomic computing are for example disclosed in the non-patent literature of Jeffrey Kephart and David Chess. The Vision of Autonomic Computing. Computer, 36(1):41-50, 2003 and M. B. Alaya, S. Matoussi, T. Monteil, and K. Drira, “Autonomic Computing System for Self-management of Machine-to-Machine Networks,” in Proceedings of the 2012 international workshop on Self-aware internet of things, ser. Self-IoT '12. ACM, 2012, pp. 25-30. However the methods and systems disclosed therein suffer from the restrictions towards automating the configuration of gateways: Computing efficient gateway configurations centrally is inapplicable because of the heterogeneity of gateway technologies and the variability of gateway tasks.